The purpose of this research is to improve our understanding of a recently discovered circular form of RNA (circular RNA or circRNA) using high-throughput sequencing data to identify and characterize these structures over a variety of contexts. Over the past two decades, studies have discovered a special form of alternative splicing (AS) that produces a circular form of RNA. This stands in contrast to normal AS which produces a linear form of RNA. Although these circRNAs have garnered considerable attention in the scientific community for their biogenesis and functions, the focus of current studies has been on the tissue-specific circRNAs that exist only in one tissue but not in other tissues or on the disease-specific circRNAs that exist in certain disease conditions, such as cancer, but not under normal conditions. This approach was conducted in the relative absence of methods that analyze a group of common circRNAs that exist in both conditions, but are more abundant in one condition relative to another (differentially expressed). Studies of common differentially expressed circRNAs between two conditions would serve as a significant first step in filling this void. One of the major applications of RNA sequencing (RNA-seq), a powerful technology for analysis of eukaryotic transcriptomes, is to detect novel (or unannotated) mRNA transcripts. Since circRNAs are novel transcripts, RNA-seq provides a perfect platform for genome-wide detection of circRNAs. Our own preliminary result from neurally-derived RNA-seq data (somata and neuropil layers of CA1 hippocampal region) has shown that over 50 circRNAs were more abundantly expressed either in the somata or in the neuropil layer. Guided by these data, the current proposal will (Aim 1) develop a novel computational method for identifying, characterizing, and quantifying differentially expressed circRNAs between any two biological conditions using RNA-seq data, and (Aim 2) develop a new web server for aggregating, cataloging, and visualizing circRNAs derived from publicly available RNA-seq datasets. This proposal will accomplish the objectives of the R15 AREA grant in: (i) supporting meritorious research; (ii) strengthening the research environment of non-research intensive institutions; and, (iii) engaging undergraduate/graduate students in bioinformatics research. The proposed work would act as a foundation for the applicant to establish a program of research aimed at facilitating circRNA studies using high-throughput sequencing data. In turn, this would provide researchers with critical information regarding circRNAs in existing high-throughput sequencing datasets. Finally, the proposed research will be used as a vehicle to engage undergraduates in multi-disciplinary bioinformatics research and better enable students from Kentucky, a traditionally underrepresented state in bioinformatics, to successfully participate in advanced biomedical research.